DocumentCode :
724290
Title :
A study on autonomous learning mechanism of Cognitive robot
Author :
Shi Tao ; Ren Hongge ; Yin Rui ; Xiang Yingfan
Author_Institution :
Coll. of Electr. Eng., Hebei United Univ., Tangshan, China
fYear :
2015
fDate :
23-25 May 2015
Firstpage :
3243
Lastpage :
3247
Abstract :
Aiming at the movement balance control problem of the robot, this paper presents a sensorimotor system Cognitive model based on operant conditioning principle, and researches the working cooperation among its interior nerve organs, so that a sensorimotor system is established. The Cognitive model can realize the sensorimotor mapping from states to actions by supervised learning, and carry out the probabilistic choice based on operant conditioning principle to actions using the action forecast evaluation results, thereby, the robot obtains the self-learning ability like human or animal through interacting, studying and training with the unknown environment, and realized the movement balance control to the robot. Consequently, the paper makes some simulation experiments on the robot, and the results indicate that this model has the better Cognitive characters and make the robot master the movement balance control skill through autonomic learning.
Keywords :
cognitive systems; learning (artificial intelligence); mobile robots; motion control; probability; action forecast evaluation; autonomic learning; autonomous learning mechanism; cognitive characters; cognitive robot model; interior nerve organs; movement balance control problem; operant conditioning principle; probabilistic choice; self-learning ability; sensorimotor mapping system; supervised learning; Animals; Basal ganglia; Biological system modeling; Brain modeling; Mobile robots; Robot sensing systems; Cognitive Model; Movement Balance Control; Operant Conditioning; Robot; Sensorimotor System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
Type :
conf
DOI :
10.1109/CCDC.2015.7162479
Filename :
7162479
Link To Document :
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